Female IT leaders urge action on gender gap in senior AI roles

A survey of UK-based female IT leaders has found widespread concern over the lack of gender diversity in senior artificial intelligence (AI) roles and the potential impact this could have on AI outputs.

The research, conducted by Cloudera, canvassed the opinions of 100 female IT decision makers and found that 68% are worried about female representation in high-level AI positions. More than half of those surveyed (56%) believe that this underrepresentation will contribute to biased outputs in AI technologies.

For 57% of respondents, AI is seen as inherently biased largely because company leaders in AI are predominantly male. This lack of diversity within the leadership ranks is considered a contributing factor to systemic inequalities being reflected in AI systems, according to the findings.

Wider gender imbalance

The concern about gender inequality in AI forms part of a broader sentiment about diversity and inclusion in the wider technology sector. The survey highlighted that 82% of female IT leaders think a gender imbalance persists throughout the industry, and 80% perceive gender equality initiatives within their organisations as little more than a tick-box exercise.

Respondents identified several barriers they believe are preventing women from entering senior AI roles, including gender bias in recruitment and promotion processes (68%), limited opportunities for upskilling (66%), and a lack of data that is suitable for AI-driven solutions (60%).

There is a strong consensus among those surveyed that more must be done to address these issues, with 89% agreeing that organisations need to improve access to AI training for women.

"Gender inequality remains a significant challenge in the technology sector. While there has been progress, we still face substantial barriers," says Mary Wells, Chief Marketing Officer at Cloudera. "Artificial Intelligence is a catalyst for positive change, with the potential to reshape businesses, industries, and economies. However, without diverse groups participating in AI development and strategy from the beginning, we risk perpetuating old biases. Our industry must make all voices central to AI innovation, ensuring that diverse perspectives drive progress as we enter this new era."

Paths to improvement

Despite the concerns expressed about existing biases in AI, the majority of those surveyed remain optimistic about the future direction of the sector. Eighty-two percent believe gender equality in AI leadership will improve in the next five years, while 79% of female IT leaders anticipate that women will be increasingly influential in shaping AI governance and strategic decision-making.

Mentoring, networking, and ongoing learning were highlighted as crucial mechanisms for empowering women in technology leadership roles. Many are also drawing on data-driven insights as they lead their teams and shape future strategies in AI development.

"IT leaders consistently emphasize the value of networking, mentorship and ongoing learnings, and many are now leveraging data to inform how they lead," says Wells. "It's not enough for diverse voices to be present in technology - their diverse perspectives and influence must extend to shaping its direction. True progress demands that all gender voices are empowered to drive decision making, because diversity of thought is essential for building a more equitable and effective future."

The findings suggest that, alongside practical actions to increase training and address recruitment biases, the future of AI leadership may depend on organisations adopting a more inclusive approach to shaping their senior teams. The views of female IT leaders reflect a call for companies to establish environments that not only support gender diversity at all levels, but also enable those voices to influence the long-term direction of technology development and implementation.

The research was collated prior to a panel session with contributions from industry figures, discussing leadership strategies and technological change in the AI sector.